Critical Essays on Canadian Public Policy: Policies to Stem the Brain Drain - Without Americanizing Canada
Bibliographic record
Abstract
Calls for Canadian policies to respond to the threat of brain drain to the United States often ignore the factors that have retarded such outflows to date. This study offers a holistic view of individual decisions to migrate. Most people care about the public services they receive as well as the taxes they pay, and many also care about the civic nature of the society they inhabit as well as the goods they can purchase privately. This perspective influences the assessment of policies as diverse as taxation, income security, public health and education, regional incentives, and social investments. A key finding is that Canadian policies should be driven by domestic objectives of equity, efficiency, and growth rather than stemming emigration or mimicking American policies. Canadian policies to spur sustained economic growth for the benefit of all Canadians should take care not to compromise the social, civic, and cultural attributes that distinguish Canada.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.010 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.036 | 0.033 |
| Scholarly communication | 0.019 | 0.006 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.017 | 0.015 |
| Insufficient payload (model declined to judge) | 0.006 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".